Initial Assessment

Online Program Selection Announcement

Online Participation Assessment

Offline Program Selection Announcement

Final  Assessment

 1. Application Completion (Google Form)

2. Proposal for International Collaboration Project (Attachment)

Successful Applicants       for Online Program

(34 participants)

1. Attendance and Participation Rate 

2. Learning Assignments on Each Lecture

Final Acceptance for Offline Program

(20 participants)

1. Attendance and Participation Rate 

2. Group Presentation on Project Development

Module 1

Digitalogy: Opening the Era of Artificial Intelligence

Prof. Junseok Hwang

(College of Engineering, SNU)

The lecture series will explore the transformative impacts of AI and emerging technology innovation on the new economy and humanity so called the Smart Economy as the future transformative Digital Economy Social Ideology. This introductory lecture will deliver and inspire the new principles and value systems as the new Pioneering Ideology for the Smart Economy, so called DIGITALOGY, to the global digital leadership how the Smart Economy and its ideology can liberalize people and society from the endless labor, competition and violence from the long-lasting-obsolete ideologies such as Dictatorial Planning Socialist Economy, Destructive Capitalism etc. This lecture will conclude with the Seven Guidelines to start the Sustainable Smart Civilization with the Smart Economy for the global leaders who are seeking for the transformative development and changes for their own economy and society.

Module 2

Digital Transformation, AI, and Finance: Cases for Financial Institutions

Prof. Han, Seung Hun

(School of Business and Technology Management, KAIST)

This lecture will explore the transformative impact of AI on the financial industry, including its integration into banks, asset management, insurance, real estate, and securities firms to enhance processes and customer experiences. It will examine the combined use of AI and blockchain in fintech to create innovative financial solutions. Additionally, the series will present real-world case studies and research examples to illustrate practical applications and future R&D directions in AI for finance, providing a comprehensive understanding of current trends and advancements.

Module 3

Introduction to Smart Infrastructure and Building Technologies

Prof. Hae-Bum Yun

(Civil, Environmental & Construction Engineering, University of Central Florida)

The current hardware-centered paradigm of civil infrastructure and buildings was mainly developed during the construction booming era of the U.S. Interstate Highway Systems in 1960s. This old paradigm is not sustainable for our rapidly aging infrastructure, nor does it ensure necessary performance of civil infrastructure. Aged infrastructure is a significant threat to national safety and security due to decreasing infrastructure resilience against nature and human-induced hazards. This lecture addresses state-of-the art technologies for smart infrastructure and buildings, empowered with crosscutting technologies including cloud computing, Internet of Things(IoT), artificial intelligence, and robotics.

Module 4

Trustworthy AI for Diversity, Equity, Inclusion, and Accessibility (DEIA)

Prof. Lee, Chul Ho

(School of Business and Technology Management, KAIST)

In this lecture, we will examine the many side effects of algorithmic decision-making, highlighting the substantial stakes for businesses associated with these side effects. Subsequently, we will discuss the algorithms to foster a deeper comprehension of how theoretical frameworks can deviate from intended outcomes. This discussion will be framed through the lens of the nature-nurture debate and the predictability-resilience paradox. Finally, we will investigate the characteristics that render algorithms trustworthy and explore strategies for mitigating the risks of rogue algorithms.

Module 5

Transforming Healthcare with AI

Prof. Lee, Junghye

(College of Engineering, SNU)

In this lecture, we will explore the transformative impact of AI on healthcare. AI is revolutionizing prediction, diagnostics, and healthcare management. We will discuss how AI algorithms enhance the accuracy and speed of disease diagnosis, with examples from radiology and pathology. The role of AI in disease prediction based on individual patient data, including genomics, and medical history, will be examined. Additionally, we will look at AI-driven innovations in drug discovery, reducing the time and cost of new drugs. AI's applications in patient health monitoring and chronic disease management will also be highlighted. Participants will gain insights into current AI advancements in healthcare and their potential to improve health outcomes and efficiencies.

Module 6

AI in the Public Sector: Use Cases & Challenges

Prof. Kim, Suk Kyoung

(School of Business and Technology Management, KAIST)

This lecture will explore the applications of AI in the public sector, examining real-world use cases such as healthcare, public safety, and smart cities. It will also discuss the challenges faced in implementing AI technologies, including data privacy, ethical concerns, and technical hurdles, and suggest strategies for overcoming these obstacles to enhance public services.

Module 7

Paradigm Change in Education in the Age of AI: From Teaching to Learning and from Mind-body Dualism to Monism

Prof. Joon-ho KANG

(College of Education, SNU)

This lecture aims to explore a new direction for future education in the age of AI. It introduces the need for a paradigm shift from the traditional standardized mass education system centered on instructors to a learner-centered personalized approach. At the same time, it discusses the metaphysical understanding of human nature transitioning from mind-body dualism to mind-body monism and how this perspective is scientifically validated by recent neuroscience. It also examines the implications of this shift for future education.

Module 8

Smart Factory 2.0 and AI: Transforming the Future of Manufacturing and Beyond 

Prof. Hayder Albayati

(Endicott College of International Studies, Woosong University)

This lecture covers smart factories, starting with current market statistics and introducing the concept and evolution of smart factories. It examines the roles of AI, IoT, big data, and robotics in enhancing manufacturing processes. Implementation strategies, including planning and technology selection, are discussed. The benefits, such as increased efficiency and cost savings, are highlighted through real-world case studies. The lecture concludes with a look at future trends, emerging technologies, and potential challenges in the smart factory landscape.

Module 9

Light and Shadow of AI on International Development

Prof. Hyeok Jeong

(Graduate School of International Studies, SNU)

The advancement of AI opens new scopes and opportunities of socio-economic development for all countries in the globe. However, the actual benefits of such technological progress are likely to be asymmetric across countries. Thus, it is unclear whether the development of AI will be a converging or diverging force for the future international development gap. In this course, we study the essence of AI in terms of economic development and explore the expected influences of AI for the national development for advanced and developing economies, and the consequential implications for international development.

Module 10

AI in Accounting:  From General Introduction to Future Trends and Innovation 

Prof. Kim, Hyungchul

(School of Business and Technology Management, KAIST)

This lecture covers AI in Accounting field. It covers general introduction of AI in accounting field and key AI technologies that are currently used in Accounting field and research. Moreover, we will discuss the benefits and challenges of using AI in accounting practice. Finally, we will learn future trends and innovation in AI in accounting.

Module 11

Towards a Safer and More Responsible AI: Directions for Policy and Regulation in the Development and Use of AI

Prof. Hyenyoung Yoon

(College of Engineering, SNU)

AI technology is being utilized in all fields of society and industry as an essential technology for the present and future, but there are also growing concerns about various social and ethical issues that AI may cause. In particular, the rapid development of generative AI in recent years has led to the emergence of large-sized AI faster than expected, and it is urgent to secure the safety and reliability of AI. As a result, governments are increasingly enacting regulations and guidelines related to AI, and global big tech companies are also introducing guidelines and solutions to show that their AI products are safe. However, the effectiveness and feasibility of these policies will need to be further discussed in the future. In this lecture, we will examine the issues that contain risks caused by AI, such as AI bias, fairness, copyright of AI creations, and hallucination, and examine the efforts of governments, international organizations, and global companies to address these issues. Throughout the course, participants will examine various aspects that need to be considered in order for AI technology to play a positive role in the development of society and industry, and gain insight into the direction of AI development and utilization that governments and companies should take in the future.

Module 12

Overview on the Essence of Generative AI and their Impacts on Future Industry Innovation 

Prof. Keungoui Kim

(School of Applied Artificial Intelligence, Handong Global University)

The advent of generative AI has had a significant impact on various aspects of our society. This rapidly growing general-purpose technology has begun to shift long-standing paradigms and demonstrate its powerful performance across industries. To align with this dynamic transition, it is important to understand the essence of generative AI and how it will be used in future innovation. In this lecture, we will explore the mechanisms of generative AI and its applications in various industries. Additionally, we will cover the impact of generative AI on future industry innovation, along with relevant policy and managerial considerations.